Long-Memory Processes: Probabilistic Properties and Statistical Methods

✍ Scribed by Jan Beran, Yuanhua Feng, Sucharita Ghosh, Rafal Kulik (auth.)

Publisher: Springer-Verlag Berlin Heidelberg
Year: 2013
Tongue: English
Leaves: 892
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Long-memory processes are known to play an important part in many areas of science and technology, including physics, geophysics, hydrology, telecommunications, economics, finance, climatology, and network engineering. In the last 20 years enormous progress has been made in understanding the probabilistic foundations and statistical principles of such processes. This book provides a timely and comprehensive review, including a thorough discussion of mathematical and probabilistic foundations and statistical methods, emphasizing their practical motivation and mathematical justification. Proofs of the main theorems are provided and data examples illustrate practical aspects. This book will be a valuable resource for researchers and graduate students in statistics, mathematics, econometrics and other quantitative areas, as well as for practitioners and applied researchers who need to analyze data in which long memory, power laws, self-similar scaling or fractal properties are relevant.

✦ Table of Contents

Front Matter....Pages I-XVII
Definition of Long Memory....Pages 1-41
Origins and Generation of Long Memory....Pages 43-106
Mathematical Concepts....Pages 107-208
Limit Theorems....Pages 209-384
Statistical Inference for Stationary Processes....Pages 385-528
Statistical Inference for Nonlinear Processes....Pages 529-554
Statistical Inference for Nonstationary Processes....Pages 555-732
Forecasting....Pages 733-752
Spatial and Space-Time Processes....Pages 753-769
Resampling....Pages 771-795
Back Matter....Pages 797-884

✦ Subjects

Statistical Theory and Methods; Probability Theory and Stochastic Processes; Statistics for Business/Economics/Mathematical Finance/Insurance; Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences; Statistics

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